Private Adaptive Gradient Methods for Convex Optimization
Hilal Asi * 1 2 John Duchi 2 3 Alireza Fallah 4 1 Omid Javidbakht 5 Kunal Talwar 5
Abstract oping private variants of stochastic gradient descent (SGD),
where algorithms guarantee differential privacy by perturb-
We study adaptive methods for differentially pri-
ing individual gradients with random noise (Duchi et al.,
...


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